Research Product

Long-term effects of organic pollutants on ecosystems were discussed on the premise that metabolism, structure, and behavior are three unifying concepts common to all levels of organization from the cell to an ecosystem. Subtle chronic problems have gone unnoticed. In general, it is difficult to study the effects of an organic contaminant on a particular system because time and resources are limiting. Therefore, it becomes necessary to extrapolate from single species or microcosm in a laboratory to effects that might occur in nature. Some laboratory to field extrapolations are acceptable while others are not, primarily because they break down at higher levels of organization. In an organism-ecosystem extrapolation the easiest concept to work with is metabolism, primarily because sensitive tools are available for assessing ecosystem level metabolic activity. Furthermore, metabolic change is correlated with structural change within an ecosystem. However, population structural measures are difficult to extrapolate to higher levels of organization and structural measures at the ecosystem level are inadequate for predictive purposes. Therefore, extrapolation from either organism or microcosm appears to be simplest in the context of metabolism. Behavior is the summation of metabolic processes and structural state. Studies of behavior have been successfully applied to individual and experimental populations but heretofore have been difficult to extrapolate to ecosystem level considerations. It follows that a synthesis of all approaches within this framework is imperative to assess any long term effects at the ecosystem level. To approach this problem it is necessary to start at the lower levels of organization and extrapolate to ecosystems paying particular attention to the relationships between the different levels of organization. Thus, one builds from the ground up and ultimately is considering ecosystem effects. The mandate to develop our capacity to extrapolate from microcosm to nature is clear. It is important to first ascertain what processes should be measured for the greatest extrapolation potential, and field verification of results should follow.